Nizomiddin Xalilov

About

Nizomiddin Xalilov

Backend & Computer Vision Engineer · Tashkent, Uzbekistan

Python and Django on the backend, YOLO and OpenCV on the camera side. Today I run the internal platforms of a US-market logistics operation: 500 trucks, 600 trailers, seven live camera feeds and a gate that opens by itself.

Nizomiddin Xalilov

Story

I am a backend engineer who ended up in computer vision because the problems in front of me needed both.

My daily work is inside a logistics company serving the US market. The trucks are real, the yard is real, and when a system misfires a driver waits at a closed gate. That constraint shaped how I build: I care less about elegant abstractions than about what happens at 3 a.m. when nobody is watching the dashboard.

Where I am strongest. Django and PostgreSQL for systems that hold operational truth — fleets, assets, contracts, invoices. Python and YOLO/OpenCV when the input is a camera instead of a form. The interesting part is usually where the two meet: a model reads a plate, an API confirms the carrier, a barrier opens.

How I got here. Computer Engineering at Fergana State Technical University, graduating with a 4.5/5.0 GPA. My thesis was a YOLOv5 model for detecting cancer markers in medical scans — work that later received a grant from the Silk Road Health Data Science community. Medical imaging taught me something logistics reinforced: a false negative and a false positive are not the same mistake, and the threshold is a business decision, not a technical one.

What I am working on now. Deepening my systems side — deployment, observability, making sure the thing I built can be handed to someone else. And German, slowly.

Experience

Experience

Jan 2024 — present · Full-time

Python Developer · System Administrator · IT Support

International logistics company (US market) · Remote · US market

I build the internal software of a fleet running 3,400+ trucks and 800 trailers: computer vision for the yard, web platforms that replaced the teams' spreadsheets, and data tools for safety, tolls and fuel. I also look after the office IT.

  • Trained YOLOv11 models for vehicle type, colour, USDOT, unit and trailer numbers (82–95% accuracy, 1,500+ images) and joined them into automated gate control.
  • Moved the fleet and asset teams from Google Sheets to a Django platform: trucks, companies, devices in use, inactive and charges, inspections, trailer agreements.
  • Built a safety events dashboard on the Motive API that counts each driver's alerts since the team's last action.
  • Automated splitting of trailer toll charges between leasing companies on file upload.
  • Analysed US diesel prices and discounts by state and station; built a weekly fleet movement report from the Genlogs API.
  • IT support: installed Windows and set up workstations, rolled out Krisp across the carrier sales office, and handled hardware issues.

Stack

Backend

Where I spend most of my time

  • Python
  • Django
  • Django REST Framework
  • PostgreSQL
  • REST API design
  • Celery
  • Redis

Computer vision & AI

Production, not notebooks

  • YOLOv5 / YOLOv11
  • OpenCV
  • PyTorch
  • MediaPipe
  • OCR / plate recognition
  • RTSP stream handling

Data

  • Pandas
  • NumPy
  • SQL optimisation
  • ETL pipelines

Infrastructure

Also my day job as sysadmin

  • Linux
  • Docker
  • Nginx
  • Gunicorn
  • Networking / VPN
  • Windows Server

Frontend

Enough to ship a full product alone

  • JavaScript (ES6+)
  • HTML / CSS
  • Django templates

Education

BSc, Computer Engineering

Fergana State Technical University

2020–2024 · GPA 4.5 / 5.0

Thesis: a YOLOv5-based detector for cancer markers in medical scans.

Languages

Uzbek
Native
English
IELTS 6.0 · B2
Russian
Fluent
German
A2 → B1, in progress

Recognition

2024 · Silk Road Health Data Science

Research grant — Silk Road Health Data Science

Awarded for the graduation project on automated cancer marker detection in medical imaging.

Certificates

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